使用 dput() 的示例 [英] Example of using dput()
问题描述
作为这里的新用户，由于不可重现，我的问题没有得到完全解答.我阅读了与生成可重现代码相关的线程，但有用.特别迷失了如何使用 dput() 函数.
Being a new user here , my questions are not being fully answered due to not being reproducible. I read the thread relating to producing reproducible code but to avail. Specifically lost on how to use the dput() function.
有人可以提供有关如何使用 dput() 使用 iris df 的分步说明，例如这将非常有帮助.
Could someone provide a step by step on how to use the dput() using the iris df for eg it would be very helpful.
推荐答案
使用 iris 数据集，它很方便地包含在 R 中，我们可以看到 dput() 有效:
Using the iris dataset, which is handily included into R, we can see how dput() works:
data(iris)
head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
现在我们可以使用 dput(iris) 获取整个数据集.在大多数情况下，不需要为 Stackoverflow 问题提供整个数据集，因为相关变量的几行就足以作为工作数据示例.
Now we can get the whole dataset using dput(iris). In most situations, a whole dataset is unnecessary to provide for a Stackoverflow question, as a few lines of the relevant variables suffice as a working data example.
有两件事可以派上用场:head() 函数只输出数据帧/矩阵的前六行.此外，R 中的索引(通过括号)允许您仅选择特定的列.
Two things come in handy: The head() function outputs only the first six rows of a dataframe/matrix. Also, the indexing in R (via brackets) allows you to select only specific columns.
因此，我们可以结合使用这两者来限制 dput() 的输出:
Therefore, we can restrict the output of dput() using a combination of these two:
dput(head(iris[, c(1, 3)]))
structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4),
Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7)), .Names = c("Sepal.Length",
"Petal.Length"), row.names = c(NA, 6L), class = "data.frame")
将为我们提供重现 iris 数据集第 1 列和第 3 列的前(最多)六行的代码.
will give us the code to reproduce the first (up to) six rows of column 1 and 3 of the iris dataset.
df <- structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4),
Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7)), .Names = c("Sepal.Length",
"Petal.Length"), row.names = c(NA, 6L), class = "data.frame")
> df
Sepal.Length Petal.Length
1 5.1 1.4
2 4.9 1.4
3 4.7 1.3
4 4.6 1.5
5 5.0 1.4
6 5.4 1.7
如果第一行不够用，我们可以跳过使用 head() 而只依赖索引:
If the first rows do not suffice, we can skip using head() and rely on indexing only:
dput(iris[1:20, c(1, 3)])
structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6,
5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1
), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4,
1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5)), .Names = c("Sepal.Length",
"Petal.Length"), row.names = c(NA, 20L), class = "data.frame")
会给我们前二十行:
df <- structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6,
5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1
), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4,
1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5)), .Names = c("Sepal.Length",
"Petal.Length"), row.names = c(NA, 20L), class = "data.frame")
> df
Sepal.Length Petal.Length
1 5.1 1.4
2 4.9 1.4
3 4.7 1.3
4 4.6 1.5
5 5.0 1.4
6 5.4 1.7
7 4.6 1.4
8 5.0 1.5
9 4.4 1.4
10 4.9 1.5
11 5.4 1.5
12 4.8 1.6
13 4.8 1.4
14 4.3 1.1
15 5.8 1.2
16 5.7 1.5
17 5.4 1.3
18 5.1 1.4
19 5.7 1.7
20 5.1 1.5
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